Turbine blade cooling has been a topic of significant interest, as increasing turbine entry temperatures result in higher cooling requirements. The present numerical method divides the blade into a finite number of elements in the span and peripheral directions and solves the heat transfer fundamental equations for convection and conduction in both directions. As inputs, the span and chord gas temperature and heat transfer coefficient distributions are required. The results include high resolution temperature prediction for the blade and coolant, at all span and chord positions. The advantages of the method include the capturing of blade temperature variation in all directions, while considering the thermal diffusion due to conduction. Mach number effects to the resulted blade and coolant temperature are highlighted, as local distribution of the gas static temperature can have a dominant role. The effect of averaging the input parameters to the predicted blade temperature is discussed and finally, different values for the material conductivity are simulated and the results are analysed.
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The dynamic inflow effect denotes the unsteady aerodynamic response to fast changes in rotor loading due to a gradual adaption of the wake. This does lead to load overshoots. The objective of the paper was to increase the understanding of that effect based on pitch step experiments on a 1.8 m diameter model wind turbine, which are performed in the large open jet wind tunnel of ForWind – University of Oldenburg. The flow in the rotor plane is measured with a 2D laser Doppler anemometer, and the dynamic wake induction factor transients in axial and tangential direction are extracted. Further, integral load measurements with strain gauges and hot-wire measurements in the near and close far wake are performed. The results show a clear gradual decay of the axial induction factors after a pitch step, giving the first direct experimental evidence of dynamic inflow due to pitch steps. Two engineering models are fitted to the induction factor transients to further investigate the relevant time constants of the dynamic inflow process. The radial dependency of the axial induction time constants as well as the dependency on the pitch direction is discussed. It is confirmed that the nature of the dynamic inflow decay is better described by two rather than only one time constant. The dynamic changes in wake radius are connected to the radial dependency of the axial induction transients. In conclusion, the comparative discussion of inductions, wake deployment and loads facilitate an improved physical understanding of the dynamic inflow process for wind turbines. Furthermore, these measurements provide a new detailed validation case for dynamic inflow models and other types of simulations.
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